The invention relates generally to the field of image reconstruction in Computed Tomography (CT) imaging systems and more particularly to the field of helical cone-beam reconstruction.
CT systems operate by projecting fan shaped or cone shaped X-ray beams through an object. The X-ray beams are generated by an X-ray source, and are generally collimated prior to passing through the object being scanned. The attenuated beams are then detected by a detector. The detector produces a signal based on the intensity of the attenuated X-ray beams, and the signals are processed to produce projection data. As is known to those skilled in the art, “projection data” refers to a single data point or a collection of data points, wherein each data point represents a line through the object to be imaged. That is, each data point represents the “integral” or “ray sum” along the line, referred to, generally, as a line integral. In CT systems, the line integrals along related lines are grouped, and each group is generally referred to as a projection.
CT systems acquire data continuously, at discrete image view frames corresponding to specific angular positions, as the source and detector rotate about the object being scanned. In helical modes of operation, the data are collected as the object is displaced by movement of the table. The resulting data set contains a large quantity of data points generally indicative of the intensity of radiation received by the detector elements at each of the angular positions. As is known by those skilled in the art, helical cone-beam CT systems have faster scan times and have the potential to cover a patient volume, with just a few gantry rotations, depending on the axial coverage of the detectors.
A computer is generally used to process and reconstruct images of the portions of the object responsible for the radiation attenuation. As will be appreciated by those skilled in the art, these images are computed by processing a series of angularly and translationally displaced projection images. This data is then reconstructed to produce the reconstructed image, which is typically displayed on a cathode ray tube or liquid crystal display, and may be printed or reproduced on film.
A number of exact reconstruction algorithms have been developed for the reconstruction of cone-beam projection data acquired in a helical mode. As is known to those skilled in the art, these algorithms are mathematically exact in the absence of noise and discretization (sampling) effects, and generally produce images of high quality when used on real data. However, known exact reconstruction algorithms are capable of covering only a narrow range of helical pitches or translation speeds of the object. As is known to those skilled in the art, higher pitches or translation speeds are sometimes required in order to meet certain clinical or inspection requirements.
In addition, exact reconstruction algorithms, in general, employ reconstruction windows spanning 360° of angular positions, generally rely upon windows spanning 180° plus the included angle of the X-ray beam (typically referred to as “a”). That is, due to redundancy in the projection data acquired for a window spanning 360° of angular positions, windows spanning 180° plus a generally suffice for image reconstruction. In general, exact reconstruction algorithms, require a scan range of at least 180+the fan angle, α, in order to perform an exact reconstruction of a central image slice. However, as is known to those skilled in the art, while performing a reconstruction of a dynamic internal tissue, such as for example a cardiac segment, in particular, only one or at the most, a few central image slices may be reconstructed (given the fact that only about 180+fan degrees of data is available for performing a cardiac segment reconstruction).
Therefore, there is a need for a technique for extending an exact helical cone-beam reconstruction algorithm to larger helical pitches as well as to adapt an exact helical cone-beam reconstruction algorithm to enable the reconstruction of a large number of images slices with good image quality, using only an angular range corresponding to a cardiac segment acquisition. In addition, there is a need for developing an efficient and accurate technique for performing helical cone-beam backprojection over PI-lines.